{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multiclass Support Vector Machine exercise\n",
    "\n",
    "*Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For more details see the [assignments page](http://vision.stanford.edu/teaching/cs231n/assignments.html) on the course website.*\n",
    "\n",
    "In this exercise you will:\n",
    "    \n",
    "- implement a fully-vectorized **loss function** for the SVM\n",
    "- implement the fully-vectorized expression for its **analytic gradient**\n",
    "- **check your implementation** using numerical gradient\n",
    "- use a validation set to **tune the learning rate and regularization** strength\n",
    "- **optimize** the loss function with **SGD**\n",
    "- **visualize** the final learned weights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Run some setup code for this notebook.\n",
    "\n",
    "import random\n",
    "import numpy as np\n",
    "from cs231n.data_utils import load_CIFAR10\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from __future__ import print_function\n",
    "\n",
    "# This is a bit of magic to make matplotlib figures appear inline in the\n",
    "# notebook rather than in a new window.\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# Some more magic so that the notebook will reload external python modules;\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CIFAR-10 Data Loading and Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (50000, 32, 32, 3)\n",
      "Training labels shape:  (50000,)\n",
      "Test data shape:  (10000, 32, 32, 3)\n",
      "Test labels shape:  (10000,)\n"
     ]
    }
   ],
   "source": [
    "# Load the raw CIFAR-10 data.\n",
    "cifar10_dir = 'cs231n/datasets/cifar-10-batches-py'\n",
    "X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir)\n",
    "\n",
    "# As a sanity check, we print out the size of the training and test data.\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Training labels shape: ', y_train.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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8mihMzsVoWySGXZp+D3CsxQwjjvxc5l9YLhezSJgkjrNJzPXA1TKkNs2iS+Oo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\nBtVm0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1z9ORjjtFM836A/sM/mhxodoriU1hiSdop1B5PbVXAIr6IcJHyv0lWK0K80jXY2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\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sVBAEs0CSaPFgF+AzNqbOnz+PC5ysKwgCP2jWmtmLJ6X3zVByNgDT6RR37xKNeuPKZdy4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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff60c10e710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize some examples from the dataset.\n",
    "# We show a few examples of training images from each class.\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "num_classes = len(classes)\n",
    "samples_per_class = 7\n",
    "for y, cls in enumerate(classes):\n",
    "    idxs = np.flatnonzero(y_train == y)\n",
    "    idxs = np.random.choice(idxs, samples_per_class, replace=False)\n",
    "    for i, idx in enumerate(idxs):\n",
    "        plt_idx = i * num_classes + y + 1\n",
    "        plt.subplot(samples_per_class, num_classes, plt_idx)\n",
    "        plt.imshow(X_train[idx].astype('uint8'))\n",
    "        plt.axis('off')\n",
    "        if i == 0:\n",
    "            plt.title(cls)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  (49000, 32, 32, 3)\n",
      "Train labels shape:  (49000,)\n",
      "Validation data shape:  (1000, 32, 32, 3)\n",
      "Validation labels shape:  (1000,)\n",
      "Test data shape:  (1000, 32, 32, 3)\n",
      "Test labels shape:  (1000,)\n"
     ]
    }
   ],
   "source": [
    "# Split the data into train, val, and test sets. In addition we will\n",
    "# create a small development set as a subset of the training data;\n",
    "# we can use this for development so our code runs faster.\n",
    "num_training = 49000\n",
    "num_validation = 1000\n",
    "num_test = 1000\n",
    "num_dev = 500\n",
    "\n",
    "# Our validation set will be num_validation points from the original\n",
    "# training set.\n",
    "mask = range(num_training, num_training + num_validation)\n",
    "X_val = X_train[mask]\n",
    "y_val = y_train[mask]\n",
    "\n",
    "# Our training set will be the first num_train points from the original\n",
    "# training set.\n",
    "mask = range(num_training)\n",
    "X_train = X_train[mask]\n",
    "y_train = y_train[mask]\n",
    "\n",
    "# We will also make a development set, which is a small subset of\n",
    "# the training set.\n",
    "mask = np.random.choice(num_training, num_dev, replace=False)\n",
    "X_dev = X_train[mask]\n",
    "y_dev = y_train[mask]\n",
    "\n",
    "# We use the first num_test points of the original test set as our\n",
    "# test set.\n",
    "mask = range(num_test)\n",
    "X_test = X_test[mask]\n",
    "y_test = y_test[mask]\n",
    "\n",
    "print('Train data shape: ', X_train.shape)\n",
    "print('Train labels shape: ', y_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Validation labels shape: ', y_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (49000, 3072)\n",
      "Validation data shape:  (1000, 3072)\n",
      "Test data shape:  (1000, 3072)\n",
      "dev data shape:  (500, 3072)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing: reshape the image data into rows\n",
    "X_train = np.reshape(X_train, (X_train.shape[0], -1))\n",
    "X_val = np.reshape(X_val, (X_val.shape[0], -1))\n",
    "X_test = np.reshape(X_test, (X_test.shape[0], -1))\n",
    "X_dev = np.reshape(X_dev, (X_dev.shape[0], -1))\n",
    "\n",
    "# As a sanity check, print out the shapes of the data\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('dev data shape: ', X_dev.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 130.64189796  135.98173469  132.47391837  130.05569388  135.34804082\n",
      "  131.75402041  130.96055102  136.14328571  132.47636735  131.48467347]\n"
     ]
    },
    {
     "data": {
      "image/png": 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58v8P8KWI+Dyj5bivkHQp8F3gnoj4XeA94KbZwzGzoYxN/hj57+bLk5t/AXwJ+GGzfSdw\ndS8RmlkvJvrML+mkZoXeQ8DTwM+B9yPio+YpbwGb+wnRzPowUfJHxMcRsQU4B9gK/N6kHUjaJmlZ\n0vLKykoyTDPr2lR3+yPifeDHwB8AGyQdvWF4DrC/pc32iFiKiKWFhYWZgjWz7oxNfkmfkbSheXwq\n8BVgL6MfAn/cPO1G4Mm+gjSz7k0ysGcTsFPSSYx+WDwaEf8s6TXgYUl/Bfw78MBkXbYN7Ol2IMjA\nhZwe1FfrG3B8Tj9nN3nQXLO2EzL5iRqb/BGxG7h4je1vMPr8b2YnIP+Fn1mlnPxmlXLym1XKyW9W\nKSe/WaVUGhnXeWfSO8CbzZdnA78crPN2juNYjuNYJ1ocvxMRn5nkgIMm/zEdS8sRsTSXzh2H43Ac\n/rXfrFZOfrNKzTP5t8+x79Ucx7Ecx7F+Y+OY22d+M5sv/9pvVqm5JL+kKyT9p6TXJd06jxiaOPZJ\nekXSS5KWB+x3h6RDkvas2naWpKcl/az5/8w5xXGHpP3NOXlJ0pUDxHGupB9Lek3Sq5L+tNk+6Dkp\nxDHoOZH0aUk/lfRyE8dfNtvPl/RckzePSDplpo4iYtB/wEmMpgH7LHAK8DJw0dBxNLHsA86eQ79f\nBC4B9qza9tfArc3jW4HvzimOO4A/G/h8bAIuaR6fDvwXcNHQ56QQx6DnhNG43NOaxycDzwGXAo8C\n1zXbvwd8a5Z+5nHl3wq8HhFvxGiq74eBq+YQx9xExLPAu8dtvorRRKgw0ISoLXEMLiIORMSLzeMP\nGU0Ws5mBz0khjkHFSO+T5s4j+TcDv1j19Twn/wzgR5JekLRtTjEctTEiDjSP3wY2zjGWmyXtbj4W\n9P7xYzVJ5zGaP+I55nhOjosDBj4nQ0yaW/sNv8si4hLgj4BvS/rivAOC0U9+5jeVz33ABYzWaDgA\n3DVUx5JOAx4DbomID1bvG/KcrBHH4OckZpg0d1LzSP79wLmrvm6d/LNvEbG/+f8Q8ATznZnooKRN\nAM3/h+YRREQcbN54R4D7GeicSDqZUcI9GBGPN5sHPydrxTGvc9L0PfWkuZOaR/I/D1zY3Lk8BbgO\n2DV0EJIWJZ1+9DHwVWBPuVWvdjGaCBXmOCHq0WRrXMMA50SjyRgfAPZGxN2rdg16TtriGPqcDDZp\n7lB3MI+7m3klozupPwf+fE4xfJZRpeFl4NUh4wAeYvTr4/8y+ux2E6M1D58Bfgb8G3DWnOL4B+AV\nYDej5Ns0QByXMfqVfjfwUvPvyqHPSSGOQc8J8PuMJsXdzegHzV+ses/+FHgd+CfgU7P047/wM6tU\n7Tf8zKrl5DerlJPfrFJOfrNKOfnNKuXkN6uUk9+sUk5+s0r9H+kBlvKdw3vSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff650aaa310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Preprocessing: subtract the mean image\n",
    "# first: compute the image mean based on the training data\n",
    "mean_image = np.mean(X_train, axis=0)\n",
    "print(mean_image[:10]) # print a few of the elements\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.imshow(mean_image.reshape((32,32,3)).astype('uint8')) # visualize the mean image\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# second: subtract the mean image from train and test data\n",
    "X_train -= mean_image\n",
    "X_val -= mean_image\n",
    "X_test -= mean_image\n",
    "X_dev -= mean_image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(49000, 3073) (1000, 3073) (1000, 3073) (500, 3073)\n"
     ]
    }
   ],
   "source": [
    "# third: append the bias dimension of ones (i.e. bias trick) so that our SVM\n",
    "# only has to worry about optimizing a single weight matrix W.\n",
    "X_train = np.hstack([X_train, np.ones((X_train.shape[0], 1))])\n",
    "X_val = np.hstack([X_val, np.ones((X_val.shape[0], 1))])\n",
    "X_test = np.hstack([X_test, np.ones((X_test.shape[0], 1))])\n",
    "X_dev = np.hstack([X_dev, np.ones((X_dev.shape[0], 1))])\n",
    "\n",
    "print(X_train.shape, X_val.shape, X_test.shape, X_dev.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SVM Classifier\n",
    "\n",
    "Your code for this section will all be written inside **cs231n/classifiers/linear_svm.py**. \n",
    "\n",
    "As you can see, we have prefilled the function `compute_loss_naive` which uses for loops to evaluate the multiclass SVM loss function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss: 9.194930\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the naive implementation of the loss we provided for you:\n",
    "from cs231n.classifiers.linear_svm import svm_loss_naive\n",
    "import time\n",
    "\n",
    "# generate a random SVM weight matrix of small numbers\n",
    "W = np.random.randn(3073, 10) * 0.0001 \n",
    "\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "print('loss: %f' % (loss, ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `grad` returned from the function above is right now all zero. Derive and implement the gradient for the SVM cost function and implement it inline inside the function `svm_loss_naive`. You will find it helpful to interleave your new code inside the existing function.\n",
    "\n",
    "To check that you have correctly implemented the gradient correctly, you can numerically estimate the gradient of the loss function and compare the numeric estimate to the gradient that you computed. We have provided code that does this for you:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerical: 5.466242 analytic: 5.466242, relative error: 3.783008e-11\n",
      "numerical: 13.903252 analytic: 13.903252, relative error: 2.970415e-11\n",
      "numerical: -49.020777 analytic: -49.020777, relative error: 3.660136e-12\n",
      "numerical: -6.378983 analytic: -6.378983, relative error: 5.469155e-13\n",
      "numerical: -18.608968 analytic: -18.608968, relative error: 4.447248e-12\n",
      "numerical: 5.194609 analytic: 5.194609, relative error: 2.075125e-11\n",
      "numerical: 1.602994 analytic: 1.602994, relative error: 7.574390e-11\n",
      "numerical: -14.919470 analytic: -14.919470, relative error: 2.042556e-11\n",
      "numerical: 14.718295 analytic: 14.718295, relative error: 1.689171e-11\n",
      "numerical: -10.096834 analytic: -10.096834, relative error: 9.186820e-12\n",
      "numerical: 9.023788 analytic: 9.023788, relative error: 1.241727e-11\n",
      "numerical: 25.250753 analytic: 25.250753, relative error: 1.774193e-12\n",
      "numerical: 21.742551 analytic: 21.742551, relative error: 1.164031e-11\n",
      "numerical: 5.026766 analytic: 5.026766, relative error: 9.241744e-11\n",
      "numerical: 1.389204 analytic: 1.389204, relative error: 5.683364e-11\n",
      "numerical: 0.397634 analytic: 0.397634, relative error: 6.236491e-10\n",
      "numerical: 16.964261 analytic: 16.964261, relative error: 1.774120e-11\n",
      "numerical: -9.143835 analytic: -9.143835, relative error: 5.540239e-12\n",
      "numerical: -1.911988 analytic: -1.911988, relative error: 3.641517e-10\n",
      "numerical: 15.950956 analytic: 15.950956, relative error: 1.961849e-11\n"
     ]
    }
   ],
   "source": [
    "# Once you've implemented the gradient, recompute it with the code below\n",
    "# and gradient check it with the function we provided for you\n",
    "\n",
    "# Compute the loss and its gradient at W.\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.0)\n",
    "\n",
    "# Numerically compute the gradient along several randomly chosen dimensions, and\n",
    "# compare them with your analytically computed gradient. The numbers should match\n",
    "# almost exactly along all dimensions.\n",
    "from cs231n.gradient_check import grad_check_sparse\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 0.0)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)\n",
    "\n",
    "# do the gradient check once again with regularization turned on\n",
    "# you didn't forget the regularization gradient did you?\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 5e1)\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 5e1)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inline Question 1:\n",
    "It is possible that once in a while a dimension in the gradcheck will not match exactly. What could such a discrepancy be caused by? Is it a reason for concern? What is a simple example in one dimension where a gradient check could fail? *Hint: the SVM loss function is not strictly speaking differentiable*\n",
    "\n",
    "**Your Answer:** *fill this in.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss: 9.194930e+00 computed in 0.116252s\n",
      "Vectorized loss: 9.194930e+00 computed in 0.012757s\n",
      "difference: -0.000000\n"
     ]
    }
   ],
   "source": [
    "# Next implement the function svm_loss_vectorized; for now only compute the loss;\n",
    "# we will implement the gradient in a moment.\n",
    "tic = time.time()\n",
    "loss_naive, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss: %e computed in %fs' % (loss_naive, toc - tic))\n",
    "\n",
    "from cs231n.classifiers.linear_svm import svm_loss_vectorized\n",
    "tic = time.time()\n",
    "loss_vectorized, _ = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss: %e computed in %fs' % (loss_vectorized, toc - tic))\n",
    "\n",
    "# The losses should match but your vectorized implementation should be much faster.\n",
    "print('difference: %f' % (loss_naive - loss_vectorized))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss and gradient: computed in 0.091713s\n",
      "Vectorized loss and gradient: computed in 0.012787s\n",
      "difference: 0.000000\n"
     ]
    }
   ],
   "source": [
    "# Complete the implementation of svm_loss_vectorized, and compute the gradient\n",
    "# of the loss function in a vectorized way.\n",
    "\n",
    "# The naive implementation and the vectorized implementation should match, but\n",
    "# the vectorized version should still be much faster.\n",
    "tic = time.time()\n",
    "_, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "tic = time.time()\n",
    "_, grad_vectorized = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "# The loss is a single number, so it is easy to compare the values computed\n",
    "# by the two implementations. The gradient on the other hand is a matrix, so\n",
    "# we use the Frobenius norm to compare them.\n",
    "difference = np.linalg.norm(grad_naive - grad_vectorized, ord='fro')\n",
    "print('difference: %f' % difference)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stochastic Gradient Descent\n",
    "\n",
    "We now have vectorized and efficient expressions for the loss, the gradient and our gradient matches the numerical gradient. We are therefore ready to do SGD to minimize the loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1500: loss 408.053018\n",
      "iteration 100 / 1500: loss 240.314310\n",
      "iteration 200 / 1500: loss 145.967070\n",
      "iteration 300 / 1500: loss 90.621803\n",
      "iteration 400 / 1500: loss 56.606570\n",
      "iteration 500 / 1500: loss 36.014659\n",
      "iteration 600 / 1500: loss 23.458049\n",
      "iteration 700 / 1500: loss 16.709597\n",
      "iteration 800 / 1500: loss 11.613450\n",
      "iteration 900 / 1500: loss 9.520974\n",
      "iteration 1000 / 1500: loss 7.332979\n",
      "iteration 1100 / 1500: loss 6.312209\n",
      "iteration 1200 / 1500: loss 6.165753\n",
      "iteration 1300 / 1500: loss 5.503118\n",
      "iteration 1400 / 1500: loss 5.463892\n",
      "That took 5.402548s\n"
     ]
    }
   ],
   "source": [
    "# In the file linear_classifier.py, implement SGD in the function\n",
    "# LinearClassifier.train() and then run it with the code below.\n",
    "from cs231n.classifiers import LinearSVM\n",
    "svm = LinearSVM()\n",
    "tic = time.time()\n",
    "loss_hist = svm.train(X_train, y_train, learning_rate=1e-7, reg=2.5e4,\n",
    "                      num_iters=1500, verbose=True)\n",
    "toc = time.time()\n",
    "print('That took %fs' % (toc - tic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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mlDOfFGWn6ITCTL2yodbvKAAAIIpQznx04uRxWlnRwNEzAACwH+XMRzedVaL0pHjd/uIm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\n/PffdfuLm1TbTEkDABzeiJc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NMLMSM0uQdL2kJ3zOBAAAMGIOv8KsT5xzPWb2GUnPqncq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\nmZmZmVkT+T/5aFLuPBd83gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff607a17090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A useful debugging strategy is to plot the loss as a function of\n",
    "# iteration number:\n",
    "plt.plot(loss_hist)\n",
    "plt.xlabel('Iteration number')\n",
    "plt.ylabel('Loss value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy: 0.377184\n",
      "validation accuracy: 0.388000\n"
     ]
    }
   ],
   "source": [
    "# Write the LinearSVM.predict function and evaluate the performance on both the\n",
    "# training and validation set\n",
    "y_train_pred = svm.predict(X_train)\n",
    "print('training accuracy: %f' % (np.mean(y_train == y_train_pred), ))\n",
    "y_val_pred = svm.predict(X_val)\n",
    "print('validation accuracy: %f' % (np.mean(y_val == y_val_pred), ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lr 1.000000e-09 reg 1.000000e+02 train accuracy: 0.144449 val accuracy: 0.159000\n",
      "lr 1.000000e-09 reg 5.000000e+04 train accuracy: 0.132633 val accuracy: 0.113000\n",
      "lr 1.000000e-07 reg 1.000000e+02 train accuracy: 0.294367 val accuracy: 0.297000\n",
      "lr 1.000000e-07 reg 5.000000e+04 train accuracy: 0.368959 val accuracy: 0.383000\n",
      "best validation accuracy achieved during cross-validation: 0.383000\n"
     ]
    }
   ],
   "source": [
    "# Use the validation set to tune hyperparameters (regularization strength and\n",
    "# learning rate). You should experiment with different ranges for the learning\n",
    "# rates and regularization strengths; if you are careful you should be able to\n",
    "# get a classification accuracy of about 0.4 on the validation set.\n",
    "learning_rates = [1e-9, 1e-7]\n",
    "regularization_strengths = [1e2, 5e4]\n",
    "\n",
    "# results is dictionary mapping tuples of the form\n",
    "# (learning_rate, regularization_strength) to tuples of the form\n",
    "# (training_accuracy, validation_accuracy). The accuracy is simply the fraction\n",
    "# of data points that are correctly classified.\n",
    "results = {}\n",
    "best_val = -1   # The highest validation accuracy that we have seen so far.\n",
    "best_svm = None # The LinearSVM object that achieved the highest validation rate.\n",
    "\n",
    "################################################################################\n",
    "# TODO:                                                                        #\n",
    "# Write code that chooses the best hyperparameters by tuning on the validation #\n",
    "# set. For each combination of hyperparameters, train a linear SVM on the      #\n",
    "# training set, compute its accuracy on the training and validation sets, and  #\n",
    "# store these numbers in the results dictionary. In addition, store the best   #\n",
    "# validation accuracy in best_val and the LinearSVM object that achieves this  #\n",
    "# accuracy in best_svm.                                                        #\n",
    "#                                                                              #\n",
    "# Hint: You should use a small value for num_iters as you develop your         #\n",
    "# validation code so that the SVMs don't take much time to train; once you are #\n",
    "# confident that your validation code works, you should rerun the validation   #\n",
    "# code with a larger value for num_iters.                                      #\n",
    "################################################################################\n",
    "\n",
    "grid_search=[(x,y) for x in learning_rates for y in regularization_strengths]\n",
    "\n",
    "for alpha, lamda in grid_search:\n",
    "    svm=LinearSVM()\n",
    "    svm.train(X_train, y_train, learning_rate=alpha, reg=lamda,\n",
    "             num_iters=1000)\n",
    "    y_pred_train = svm.predict(X_train)\n",
    "    y_pred_val = svm.predict(X_val)\n",
    "    training_accuracy =  np.mean(y_pred_train==y_train)\n",
    "    validation_accuracy = np.mean(y_pred_val==y_val)\n",
    "    results[alpha, lamda] = (training_accuracy,\n",
    "                            validation_accuracy)\n",
    "    if best_val < validation_accuracy:\n",
    "        best_val = validation_accuracy\n",
    "        best_svm = svm\n",
    "    \n",
    "################################################################################\n",
    "#                              END OF YOUR CODE                                #\n",
    "################################################################################\n",
    "    \n",
    "# Print out results.\n",
    "for lr, reg in sorted(results):\n",
    "    train_accuracy, val_accuracy = results[(lr, reg)]\n",
    "    print('lr %e reg %e train accuracy: %f val accuracy: %f' % (\n",
    "                lr, reg, train_accuracy, val_accuracy))\n",
    "    \n",
    "print('best validation accuracy achieved during cross-validation: %f' % best_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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v2AvAoIjYGbgTuDhtuzHwY2APYHfgx5I2KnS8UpqcLgO+CLwHEBEvAvuWsJ2Z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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff607eb2d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the cross-validation results\n",
    "import math\n",
    "x_scatter = [math.log10(x[0]) for x in results]\n",
    "y_scatter = [math.log10(x[1]) for x in results]\n",
    "\n",
    "# plot training accuracy\n",
    "marker_size = 100\n",
    "colors = [results[x][0] for x in results]\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, edgecolors='black')\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 training accuracy')\n",
    "\n",
    "# plot validation accuracy\n",
    "colors = [results[x][1] for x in results] # default size of markers is 20\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, edgecolors='black')\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 validation accuracy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linear SVM on raw pixels final test set accuracy: 0.359000\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the best svm on test set\n",
    "y_test_pred = best_svm.predict(X_test)\n",
    "test_accuracy = np.mean(y_test == y_test_pred)\n",
    "print('linear SVM on raw pixels final test set accuracy: %f' % test_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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oFFvgtcp82YySUNZAlY5noB97FmjZUUK1sFJQ8vUFqM6i9yvr9uRdiqa4j+vs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\n3V0cz+0x7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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff607c12090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the learned weights for each class.\n",
    "# Depending on your choice of learning rate and regularization strength, these may\n",
    "# or may not be nice to look at.\n",
    "w = best_svm.W[:-1,:] # strip out the bias\n",
    "w = w.reshape(32, 32, 3, 10)\n",
    "w_min, w_max = np.min(w), np.max(w)\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "for i in range(10):\n",
    "    plt.subplot(2, 5, i + 1)\n",
    "      \n",
    "    # Rescale the weights to be between 0 and 255\n",
    "    wimg = 255.0 * (w[:, :, :, i].squeeze() - w_min) / (w_max - w_min)\n",
    "    plt.imshow(wimg.astype('uint8'))\n",
    "    plt.axis('off')\n",
    "    plt.title(classes[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inline question 2:\n",
    "Describe what your visualized SVM weights look like, and offer a brief explanation for why they look they way that they do.\n",
    "\n",
    "**Your answer:** \n",
    "\n",
    "The SVM weights seem to have picked the dominant colour of each class. They are strictly dependent on the examples that the classifier has seen during training."
   ]
  }
 ],
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   "display_name": "Python 2",
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    "name": "ipython",
    "version": 2
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
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